What role does AI play in reward and benefits?

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Need to know:

  • Artificial intelligence (AI) is already starting to impact the world of benefits and reward, in areas such as benefits selection, administration and modelling potential strategies.
  • Employees can also gain through personalised recommendations and support with questions.
  • But concerns remain over data security and the lack of emotional intelligence in AI.

The rise of artificial intelligence (AI) has made plenty of headlines recently, and this is likely to continue over the coming year. In the benefits and reward space, providers are now starting to integrate its capabilities into their offerings, and employers are starting to benefit.

AI is already helping provide actionable insights which can help employers formulate approaches, says Gethin Nadin, chief innovation officer at Zellis and Benefex. “It means they can be more proactive in their reward and benefits strategies, react faster to changing trends and create more compelling stories to share with the wider business,” he says. “AI-driven data insights can identify which benefits are working well, which need to be changed and which may need some additional communications support.”

An example of this is in the health arena, where AI can help to provide personalised health and wellbeing support to employees. Ian Talbot, chief executive officer (CEO) of Healix Health. says: “For an individual who has a predisposition for anxiety and stress, for example, AI can help learn the content which is most engaging and useful to them, before providing relevant signposting towards health and wellbeing information to help them manage their symptoms better.”

Conversational AI can also be used to provide instant assessments for employees, directing them to sources of support if needed, without the need to speak to their employer, he adds.

AI and employee data

AI is starting to influence the benefits space in other ways, too. Scot Marcotte, chief technology officer at Buck, a Gallagher company, points to its ability to help employers model potential scenarios. “It can gather disparate datasets, rapidly apply what if scenarios and benchmark data, allowing employers to explore issues related to diversity, equity and inclusion or analyse compensation trends,” he says.

In the insurance space, AI is used in predictive analytics to anticipate future benefits, needs and trends. Rory Yates, senior vice president, corporate strategy, at EIS, says: “By analysing historical data and market trends, AI algorithms can forecast factors like healthcare costs, usage rates and employee preferences. This helps employers to proactively adjust benefits programmes, negotiate better rates with vendors and make informed decisions on plan modifications.”

There is also the potential for AI to be used as a checking mechanism to identify issues that could potentially be missed by humans, says Georgios Michalakidis, chief technology officer at Vivup. “For instance, it could ensure that salary sacrifice doesn’t allow an employee to fall below the national living wage,” he says. “It can also monitor and flag potential employee fraud, which is something that employers often overlook.”

Personalised benefits

AI is also starting to filter through into tangible benefits for employees. It is already helping businesses to provide more personalised benefits journeys for employees, allowing them to understand and select the most relevant to them, says Nadin. “AI-driven educational content is helping to dispel myths and add clarity around what some popular benefits are for, and whether an employee should choose them,” he says.

It can also help employees when they have queries, which has the added benefit of reducing the burden on reward and benefits teams. “Rather than clicking around for information, employees will be able to ask an AI assistant to manage these actions on their behalf,” explains Michalakidis. “Customised user content and recommendations on benefits can either be delivered to an inbox or visible on the platform across an employee’s preferred channels.”

Employees themselves will become increasingly comfortable with the use of AI in the benefits space, he adds. “Just as we’ve grown and adapted to the Alexa and Siri moments in the evolution of technology, using AI tools like ChatGPT will be a natural progression for employees,” he predicts. “It can support the most diverse set of users working in public and private sector organisations with very different needs.”

Human interactions

Yet there are some areas where the human touch is still required. Financial advice and planning is one area where the use of AI can only help so far, says Sam Lathey, CEO at Bippit. “Finances are, ultimately, intensely personal: they’re driven as much by psychology and our embedded relationship with money as debts and assets,” he explains. “It’s very hard for automated systems to take into account all the considerations that go into providing professional, personal finance support and integrate them in a way that works for the individual.

“That doesn’t mean that AI can’t be very useful in this space. To make good financial decisions, people need to be thinking and engaging with their money and aware of what options are available. It’s also very useful to have insight, such as spending data analysis, to hand. In these areas, AI can, and will, be used to give people additional knowledge, skills and awareness and orient them towards taking greater control of their financial lives.”

Reward strategy transformation

There is also potential for AI to start to influence other areas, even if it has yet to infiltrate them. Grant Price, CEO of workplace and AI strategy consultant YOHO Workplace Strategy, believes it could start to play more of a role in shaping reward strategies. “Sooner rather than later, there is no doubt that AI will transform nearly all areas of employee reward and benefits as it will allow organisations to clearly optimise and customise their total reward programmes,” he says.

This could see it move into areas such as equitable compensation analysis, predictive retention analytics and the automation of routine administration. “Other major areas of opportunity are using data-driven insights for optimised compensation structures and levels, real-time support for manager decisions, benchmarking against industry peers and overall reward programme strategy optimisation,” Price adds.

There is also potential for greater analysis of benefits take-up in general. “Healix’s data shows employee demand for non-standard benefits soaring,” says Talbot. “AI has the potential to allow [employers] to analyse which benefits employees have taken up, collect any feedback on how these have supported them and use this information to shape the benefits that they roll out in the future.”

This should open the door for even more personalised benefits experiences, adds Nadin. “Employers are increasingly opting for benefits technology that lets them target communications by behaviour, demographics, interests and locations, and track the success of communications campaigns to see what’s resonating, and what isn’t,” he says. “AI is now starting to assist in that already and will expand more in 2024.”

Sensitive data

Yet there are also warnings around the use of AI in the reward and benefits space. “Businesses should tread carefully with the sensitive reward and benefits data entrusted to them,” says Marcotte. “Specifically, they must limit the exposure of ‘closed’ pay and benefits data to ‘open’ AI systems and keep AI models enclosed within organisations to adequately protect employee data.”

Ben Travers, a partner in AI and IP at law firm Knights, highlights the lack of emotional intelligence when relying on AI. “When it comes to benefits, as with other elements of HR, emotional intelligence can be key to understanding the nuance of a situation and in communicating information to teams,” he says.

“Based on current AI capabilities, it is essential in my view that there is a human backup when it comes to decision-making in potentially sensitive fields such as HR. There needs to be a person who can justify, or indeed override, the AI decision if appropriate.”